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I've been using the old cudahashcat 2.x until I reinstalled my system. I realized I cann't find any newer release on cudahascat so I assume it is included in hashcat but when I look at their github it seems to be only the OpenCL is included. So my question being do I need to find cudahashcat mod somewhere or should I just use the official hashcat 4.x?

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You should definitely just use the latest hashcat from hashcat.net.

There have been many changes and improvements since 'cudaHashcat' / 'oclHashcat' / 'hashcat' (CPU) were all merged into the new unified 'hashcat'.

All devices now require OpenCL - even CPU - and CUDA is completely gone.

  • What happens if I have an older GPU/CPU that doesn't really run OpenCL (well)? I have a GF116 [GeForce GTS 450 Rev. 2] in this particular machine. – Aero Wang Nov 23 '17 at 2:56
  • If the card is still supported by the manufacturer (current drivers), and OpenCL works generally, then hashcat should work. – Royce Williams Nov 23 '17 at 4:09
  • No it is not supported... – Aero Wang Nov 23 '17 at 6:52
  • Ah, bummer. Only cards supported by current drivers are supported by hashcat. (It's a little OT, but you can get a much newer card quite cheaply used - even a GTX750Ti would be significantly better, a GTX 970 should also be relatively affordable.) – Royce Williams Nov 24 '17 at 2:40
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No, neither the hashcat binaries download nor by hashcat download via Kali Linux repositories include the Nvidia CUDA Toolkit; the Nvidia CUDA Toolkit must be downloaded separately- feel free to review my full gist on GitHub. Hope that helps!

Installing the Nvidia CUDA Toolkit 10.0

Installing the Nvidia CUDA Toolkit 10.0 for Ubuntu 18.04 - Option A (Recommended)

  1. sudo apt update && apt dist-upgrade -y && reboot
  2. lspci -v
  3. sudo apt install -y ocl-icd-libopencl1 nvidia-driver nvidia-cuda-toolkit.
  4. nvidia-smi
  5. Run sudo hashcat -I or sudo hashcat --benchmark for benchmarks.

Installing the Nvidia CUDA Toolkit 10.0 for Ubuntu 18.04 - Option B

  1. Go to Nvidia CUDA Toolkit 10.0 for Ubuntu 18.04.
  2. Select the following Select Target Platform Window: Linux > X86_64 > Ubuntu > 18.04 > runfile (local)
    • To check your OS architecture run uname -a it should return "x_86_64" within the terminal display.
  3. Download the Base Installer (2.0 GB) by click on the Download button.
  4. Access Terminal and close X Server to avoid errors while updating nVidia driver by running sudo init 3; a black-screen will appear and prompt you to enter your Ubuntu username and password- please enter.
  5. After logging-in, run cd ~/Downloads.
  6. Run sudo sh cuda_10.0.130_410.48_linux.run
  7. Scroll down to accept the conditions by holding down the "Return" key or space-bar- upon scrolling to the bottom, type: accept; alternatively, you can hit 'CTRL + D' to bypass scrolling.
  8. Install the CUDA 10.0 Toolkit by enter y
  9. Do you want to Install the OpenGL Libraries y
  10. Do you want to run nvidia-xconfig? Enter y
  11. Install the CUDA Toolkit? Enter y
  12. Unless otherwise preferred, hit the "Return" key to enter the specified default absolute-path (e.g. /usr/local/cuda-10.0).
  13. Enter y to install a symbolic link at /usr/local/cuda.
  14. Enter y to Install the CUDA 10.0 Samples
  15. Hit the "Return" key to enter CUDA Samples default location-path (e.g. /home/alexanderjsingleton).
  16. After the install, open the X Server by running sudo init 5; if for whatever reason you're unable to reboot the computer after installing the CUDA 10.0 Toolkit, turn-off the computer and reboot- remember to click on the Settings icon and select "Ubuntu on wayland" before entering the username and password.
  17. Access terminal and enter the following commands in sequence:
    • sudo add-apt-repository ppa:graphics-drivers/ppa
    • sudo apt-get update
    • sudo apt-get install mesa-common-dev
    • sudo apt-get install freeglut3-dev
  18. Reboot the computer by running sudo shutdown -r now

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